Junjun Liu, Frederik Johannes Verweij, Guillaume van Niel, Thierry Galli, Lydia Danglot, Philippe Bun
{"title":"ExoJ - a Fiji/ImageJ2 plugin for automated spatiotemporal detection and analysis of exocytosis.","authors":"Junjun Liu, Frederik Johannes Verweij, Guillaume van Niel, Thierry Galli, Lydia Danglot, Philippe Bun","doi":"10.1242/jcs.261938","DOIUrl":null,"url":null,"abstract":"<p><p>Exocytosis is a dynamic physiological process that enables the release of biomolecules to the surrounding environment via the fusion of membrane compartments to the plasma membrane. Understanding its mechanisms is crucial, as defects can compromise essential biological functions. The development of pH-sensitive optical reporters alongside fluorescence microscopy enables the assessment of individual vesicle exocytosis events at the cellular level. Manual annotation represents, however, a time-consuming task that is prone to selection biases and human operational errors. Here, we introduce ExoJ, an automated plugin based on Fiji/ImageJ2 software. ExoJ identifies user-defined genuine populations of exocytosis events, recording quantitative features including intensity, apparent size and duration. We designed ExoJ to be fully user-configurable, making it suitable for studying distinct forms of vesicle exocytosis regardless of the imaging quality. Our plugin demonstrates its capabilities by showcasing distinct exocytic dynamics among tetraspanins and vesicular SNARE protein reporters. Assessment of performance on synthetic data shows that ExoJ is a robust tool that is capable of correctly identifying exocytosis events independently of signal-to-noise ratio conditions. We propose ExoJ as a standard solution for future comparative and quantitative studies of exocytosis.</p>","PeriodicalId":15227,"journal":{"name":"Journal of cell science","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of cell science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1242/jcs.261938","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/23 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Exocytosis is a dynamic physiological process that enables the release of biomolecules to the surrounding environment via the fusion of membrane compartments to the plasma membrane. Understanding its mechanisms is crucial, as defects can compromise essential biological functions. The development of pH-sensitive optical reporters alongside fluorescence microscopy enables the assessment of individual vesicle exocytosis events at the cellular level. Manual annotation represents, however, a time-consuming task that is prone to selection biases and human operational errors. Here, we introduce ExoJ, an automated plugin based on Fiji/ImageJ2 software. ExoJ identifies user-defined genuine populations of exocytosis events, recording quantitative features including intensity, apparent size and duration. We designed ExoJ to be fully user-configurable, making it suitable for studying distinct forms of vesicle exocytosis regardless of the imaging quality. Our plugin demonstrates its capabilities by showcasing distinct exocytic dynamics among tetraspanins and vesicular SNARE protein reporters. Assessment of performance on synthetic data shows that ExoJ is a robust tool that is capable of correctly identifying exocytosis events independently of signal-to-noise ratio conditions. We propose ExoJ as a standard solution for future comparative and quantitative studies of exocytosis.